3 citations · 9 across the 6 of their papers we have counts for
6 papers
Aligning Academia with Industry: An Empirical Study of Industrial Needs and Academic Capabilities in AI-Driven Software Engineering
Hang Yu, Yuzhou Lai, Li Zhang +6
The rapid advancement of large language models (LLMs) is fundamentally reshaping software engineering (SE), driving a paradigm shift in both academic research and industrial practi…
Generating Project-Specific Test Cases with Requirement Validation Intention
Binhang Qi, Yun Lin, Xinyi Weng +5
Test cases are valuable assets for maintaining software quality. State-of-the-art automated test generation techniques typically focus on maximizing program branch coverage or tran…
GraphCodeAgent: Dual Graph-Guided LLM Agent for Retrieval-Augmented Repo-Level Code Generation
Jia Li, Xianjie Shi, Kechi Zhang +10
Writing code requires significant time and effort in software development. To automate this process, researchers have made substantial progress for code generation. Recently, large…
LONGCODEU: Benchmarking Long-Context Language Models on Long Code Understanding
Jia Li, Xuyuan Guo, Lei Li +7
Current advanced long-context language models offer great potential for real-world software engineering applications. However, progress in this critical domain remains hampered by…
Exploring and Unleashing the Power of Large Language Models in Automated Code Translation
Zhen Yang, Fang Liu, Zhongxing Yu +7
Code translation tools (transpilers) are developed for automatic source-to-source translation. Although learning-based transpilers have shown impressive enhancement against rule-ba…
Automated Commit Message Generation with Large Language Models: An Empirical Study and Beyond
Pengyu Xue, Linhao Wu, Zhongxing Yu +5
Commit Message Generation (CMG) approaches aim to automatically generate commit messages based on given code diffs, which facilitate collaboration among developers and play a criti…